I am a Data Scientist and Data Scientist Team Manager at CyberAgent, Inc.

I am interested in Econometrics, Causal Inference, A/B test and Reinforcement Learning. Kaggle Master

• Data Science
• data science team management / building
• econometrics
• causal inference
• A/B test
• Reinforcement Learning
• Python, Scala
• Kaggle

• AI Predictor, 2018.06 - 2018.10
  • Building prediction models for ad platform
• CA Dyve, 2018.10 - 2019.09
  • Building prediction models for ad platform
  • A/B testing
  • Ad Management
• Dynalyst, 2019.09 - present
  • data science team manager / product manager
  • A/B testing
  • Building an A/B testing platform for ad creatives, Bandit Algorithms
  • Building recommendation engines, prediction models
• Data Science Center, 2021.10 - present

• Department of Statistics, Graduate school of Economics, University of Tokyo(M.A.), 2016.04 - 2018.03
  • Research Topics: Causal Inference(RDD), Econometrics, Statistics
  • Supervisor: Prof. Katsumi Shimotsu
• Department of Economics, Graduate school of Economics, University of Tokyo(B.A.) 2012.04 - 2016.03
  • Research Topics: Econometrics, Game Theory
  • Supervisor: Prof. Katsumi Shimotsu

• Abe, Kenshi, and Yusuke Kaneko. "Off-Policy Exploitability-Evaluation in Two-Player Zero-Sum Markov Games." AAMAS 2021 (Full Paper)
• Morishita, Gota, et al. "Online Learning for Bidding Agent in First Price Auction." Workshop on Reinforcement Learning in Games in Thirty-Fourth AAAI Conference on Artificial Intelligence. 2020.

• Kato, Masahiro, and Yusuke Kaneko. "Off-policy evaluation of bandit algorithm from dependent samples under batch update policy." arXiv preprint arXiv:2010.13554 (2020).

• 伊藤寛武, and 金子雄祐. "リターゲティング広告配信における不連続回帰を用いたリフト効果分析." 人工知能学会全国大会論文集 第 36 回 (2022). 一般社団法人 人工知能学会, 2022.(全国大会優秀賞受賞)
• 阿部拳之, 金子雄祐: “二人零和マルコフゲームにおけるオフ方策評価のためのQ学習”, 第25回ゲームプログラミングワークショップ, 2020.

https://www.kaggle.com/ykaneko1992

Kaggle Master

• "clustering for private interest-based advertising" & "learning a logistic model from aggregated data"
  • KDD2021 参加報告&論文読み会 2021/09/24 (slide)
• 広告クリエイティブ最適化と評価のためのBandit
  • CF + FinML勉強会 2021/03/13 (slide)

• ビジネス(の人)的に嬉しいコンペ開催のやり方
  • Discovery DataScience Meet up (DsDS) #1 2020/11/13 (slide)